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Explainability and interpretability are important aspects in ensuring the security of decisions made by intelligent systems (review article)

Научно-технический вестник информационных технологий, механики и оптики
The issues of trust in decisions made (formed) by intelligent systems are becoming more and more relevant. A systematic review of Explicable Artificial Intelligence (XAI) methods and tools aimed at bridging the gap between the complexity of neural ...
D. N. Biryukov, A. S. Dudkin
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Explainable AI: A Review of Machine Learning Interpretability Methods

Entropy, 2020
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption, with machine learning systems demonstrating superhuman performance in a significant number of tasks.
Pantelis Linardatos, Vasilis Papastefanopoulos, Sotiris Kotsiantis   +2 more
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Interpretable Ensemble-Based Intrusion Detection Using Feature Selection on the ToN_IoT Dataset

JISA (Jurnal Informatika dan Sains)
With With the rapid growth of IoT, securing interconnected devices against cyber threats has become critical. IoT datasets such as ToN-IoT are often high-dimensional, which poses challenges for efficient and accurate intrusion detection.
Vaman Shakir Sulaiman, Firas Mahmood Mustafa   +1 more
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Essential properties and explanation effectiveness of explainable artificial intelligence in healthcare: A systematic review

Heliyon, 2023
Background: Significant advancements in the field of information technology have influenced the creation of trustworthy explainable artificial intelligence (XAI) in healthcare.
Jinsun Jung, Hyungbok Lee, Hyunggu Jung, Hyeoneui Kim   +3 more
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Skin Lesion Classification: A Deep Learning Approach with Local Interpretable Model-Agnostic Explanations (LIME) for Explainable Artificial Intelligence (XAI)

JOIV: International Journal on Informatics Visualization
The classification of skin cancer is crucial as the chance of survival increases significantly with timely and accurate treatment. Convolution Neural Networks (CNNs) have proven effective in classifying skin cancer. However, CNN models are often regarded
Sin Yi Hong, Lih Poh Lin
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Analysis of Customer Churn Classification for Sinarmas Syariah Lhokseumawe Insurance Services Using Deep Learning Tabnet and Explainable AI

Journal of Applied Informatics and Computing
Customer churn is a major challenge in the insurance industry because it directly affects customer retention, business sustainability, and company profitability.
Syarifah Muliana, Taufiq Taufiq, Munirul Ula   +2 more
doaj   +1 more source

Trustworthy XAI and Application

CoRR
Artificial Intelligence (AI) is an important part of our everyday lives. We use it in self-driving cars and smartphone assistants. People often call it a "black box" because its complex systems, especially deep neural networks, are hard to understand. This complexity raises concerns about accountability, bias, and fairness, even though AI can be quite ...
Nasim, MD Abdullah Al, Ferdous, A. S. M Anas, Rashid, Abdur, Soshi, Fatema Tuj Johura, Biswas, Parag, Biswas, Angona, Gupta, Kishor Datta   +6 more
openaire   +2 more sources

Designer-User Communication for XAI: An epistemological approach to discuss XAI design

CoRR, 2021
Artificial Intelligence is becoming part of any technology we use nowadays. If the AI informs people's decisions, the explanation about AI's outcomes, results, and behavior becomes a necessary capability. However, the discussion of XAI features with various stakeholders is not a trivial task.
Juliana Jansen Ferreira, Mateus de Souza Monteiro   +1 more
openaire   +2 more sources

Explainable Ensemble Framework for Cyber Threat Detection in UAV Networks [PDF]

E3S Web of Conferences
Unmanned Aerial Vehicles (UAVs) serve an essential function in various civilian, commercial, and military applications, but their reliance on wireless communication, onboard sensors, and ground control systems make them vulnerable to a comprehensive set ...
Chidimma Chima Caleb, Asuquo Philip, Nnanna Ihemereze Chijioke, Enang Imoh Okon, Agbor Bright Agbor, Stephen Bliss Utibe-Abasi, Bassey Vivian Abel   +6 more
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Explaining Machine Learning Solutions for Histopathology Images

Applied Medical Informatics, 2021
Machine Learning may have huge benefits for the medical practice. The problem with accepting the machine learning solutions is that it is difficult for the medical staff to understand their decision and because of this they are not able to trust them as ...
Cătălin Mihai PESECAN, Lăcrămioara STOICU-TIVADAR   +1 more
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